Søren Hauberg

According to our database, Søren Hauberg authored at least 95 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections.

Marco Miani, Hrittik Roy, Søren Hauberg

CoRR, 2024

Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information.

Marco Miani, Lorenzo Beretta, Søren Hauberg

CoRR, 2024

Decoder ensembling for learned latent geometries.

Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg

CoRR, 2024

A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences.

Miguel González Duque, Richard Michael, Simon Bartels, Yevgen Zainchkovskyy, Søren Hauberg, Wouter Boomsma

CoRR, 2024

Reparameterization invariance in approximate Bayesian inference.

Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg

CoRR, 2024

Gradients of Functions of Large Matrices.

Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg

CoRR, 2024

A Continuous Relaxation for Discrete Bayesian Optimization.

Richard Michael, Simon Bartels, Miguel González Duque, Yevgen Zainchkovskyy, Jes Frellsen, Søren Hauberg, Wouter Boomsma

CoRR, 2024

Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification.

Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Frederik Warburg, Aasa Feragen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Accurate Computation of the Logarithm of Modified Bessel Functions on GPUs.

Andreas Plesner, Hans Henrik Brandenborg Sørensen, Søren Hauberg

Proceedings of the 38th ACM International Conference on Supercomputing, 2024

Improving Adversarial Energy-Based Model via Diffusion Process.

Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Neural Contractive Dynamical Systems.

Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Reactive motion generation on learned Riemannian manifolds.

Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo

Int. J. Robotics Res., September, 2023

Identifying latent distances with Finslerian geometry.

Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg

Trans. Mach. Learn. Res., 2023

Variational Point Encoding Deformation for Dental Modeling.

Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergaard, Søren Hauberg

CoRR, 2023

Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty.

Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Aasa Feragen, Frederik Warburg

CoRR, 2023

Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval.

Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Masked Pre-training and the Marginal Likelihood.

Pablo Moreno-Muñoz, Pol Garcia Recasens, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Riemannian Laplace approximations for Bayesian neural networks.

Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Taste: A Multimodal Wine Dataset.

Thoranna Bender, Simon Møe Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge J. Belongie, Frederik Warburg

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Cholesky Gaussian Processes.

Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization.

Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera

IEEE Robotics Autom. Lett., 2022

Probabilistic thermal stability prediction through sparsity promoting transformer representation.

Yevgen Zainchkovskyy, Jesper Ferkinghoff-Borg, Anja Bennett, Thomas Egebjerg, Nikolai Lorenzen, Per Greisen Jr., Søren Hauberg, Carsten Stahlhut

CoRR, 2022

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results.

Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane

CoRR, 2022

Is an encoder within reach?

Helene Hauschultz, Rasmus Berg Palm, Pablo Moreno-Muños, Nicki Skafte Detlefsen, Andrew Allan du Plessis, Søren Hauberg

CoRR, 2022

Visualizing Riemannian data with Rie-SNE.

Andri Bergsson, Søren Hauberg

CoRR, 2022

Benchmarking Generative Latent Variable Models for Speech.

Jakob D. Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe

CoRR, 2022

Robust uncertainty estimates with out-of-distribution pseudo-inputs training.

Pierre Segonne, Yevgen Zainchkovskyy, Søren Hauberg

CoRR, 2022

Probabilistic spatial transformer networks.

Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg

Proceedings of the Uncertainty in Artificial Intelligence, 2022

ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results.

Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane

Proceedings of the Topological, 2022

Revisiting Active Sets for Gaussian Process Decoders.

Pablo Moreno-Muñoz, Cilie W. Feldager, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Laplacian Autoencoders for Learning Stochastic Representations.

Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte Detlefsen, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry.

Miguel González Duque, Rasmus Berg Palm, Søren Hauberg, Sebastian Risi

Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

Model-agnostic out-of-distribution detection using combined statistical tests.

Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Pulling back information geometry.

Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning.

Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Multi-chart flows.

Dimitris Kalatzis, Johan Ziruo Ye, Jesper Wohlert, Søren Hauberg

CoRR, 2021

Learning Riemannian Manifolds for Geodesic Motion Skills.

Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Bounds all around: training energy-based models with bidirectional bounds.

Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data.

Martin Jørgensen, Søren Hauberg

Proceedings of the 38th International Conference on Machine Learning, 2021

Hierarchical VAEs Know What They Don't Know.

Jakob Drachmann Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe

Proceedings of the 38th International Conference on Machine Learning, 2021

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval.

Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Spontaneous Symmetry Breaking in Data Visualization.

Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Geometrically Enriched Latent Spaces.

Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Parallel <i>QR</i> Factorization of Block-Tridiagonal Matrices.

Alfredo Buttari, Søren Hauberg, Costy Kodsi

SIAM J. Sci. Comput., 2020

What is a meaningful representation of protein sequences?

Nicki Skafte Detlefsen, Søren Hauberg, Wouter Boomsma

CoRR, 2020

Reparametrization Invariance in non-parametric Causal Discovery.

Martin Jørgensen, Søren Hauberg

CoRR, 2020

Probabilistic Spatial Transformers for Bayesian Data Augmentation.

Pola Schwöbel, Frederik Warburg, Martin Jørgensen, Kristoffer H. Madsen, Søren Hauberg

CoRR, 2020

Can You Trust Predictive Uncertainty Under Real Dataset Shifts in Digital Pathology?

Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, Anders B. Dahl

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Variational Autoencoders with Riemannian Brownian Motion Priors.

Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg

Proceedings of the 37th International Conference on Machine Learning, 2020

Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition.

Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Expected path length on random manifolds.

David Eklund, Søren Hauberg

CoRR, 2019

Reliable training and estimation of variance networks.

Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Explicit Disentanglement of Appearance and Perspective in Generative Models.

Nicki Skafte Detlefsen, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models.

Anton Mallasto, Søren Hauberg, Aasa Feragen

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Fast and Robust Shortest Paths on Manifolds Learned from Data.

Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Geodesic Clustering in Deep Generative Models.

Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, Søren Hauberg

CoRR, 2018

Only Bayes should learn a manifold (on the estimation of differential geometric structure from data).

Søren Hauberg

CoRR, 2018

Latent Space Oddity: on the Curvature of Deep Generative Models.

Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg

Proceedings of the 6th International Conference on Learning Representations, 2018

Directional Statistics with the Spherical Normal Distribution.

Søren Hauberg

Proceedings of the 21st International Conference on Information Fusion, 2018

Deep Diffeomorphic Transformer Networks.

Nicki Skafte Detlefsen, Oren Freifeld, Søren Hauberg

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Transformations Based on Continuous Piecewise-Affine Velocity Fields.

Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich, John W. Fisher III

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data.

Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg

Proceedings of the Geometric Science of Information - Third International Conference, 2017

Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning.

Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Scalable Robust Principal Component Analysis Using Grassmann Averages.

Søren Hauberg, Aasa Feragen, Raffi Enficiaud, Michael J. Black

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Principal Curves on Riemannian Manifolds.

Søren Hauberg

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Data-driven forward model inference for EEG brain imaging.

Sofie Therese Hansen, Søren Hauberg, Lars Kai Hansen

NeuroImage, 2016

A Locally Adaptive Normal Distribution.

Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Open Problem: Kernel methods on manifolds and metric spaces. What is the probability of a positive definite geodesic exponential kernel?

Aasa Feragen, Søren Hauberg

Proceedings of the 29th Conference on Learning Theory, 2016

Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation.

Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, Lars Kai Hansen

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

A Random Riemannian Metric for Probabilistic Shortest-Path Tractography.

Søren Hauberg, Michael Schober, Matthew G. Liptrot, Philipp Hennig, Aasa Feragen

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple.

Oren Freifeld, Søren Hauberg, Kayhan N. Batmanghelich, John W. Fisher III

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Geodesic exponential kernels: When curvature and linearity conflict.

Aasa Feragen, François Lauze, Søren Hauberg

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Metrics for Probabilistic Geometries.

Alessandra Tosi, Søren Hauberg, Alfredo Vellido, Neil D. Lawrence

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers.

Michael Schober, Niklas Kasenburg, Aasa Feragen, Philipp Hennig, Søren Hauberg

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Grassmann Averages for Scalable Robust PCA.

Søren Hauberg, Aasa Feragen, Michael J. Black

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Model Transport: Towards Scalable Transfer Learning on Manifolds.

Oren Freifeld, Søren Hauberg, Michael J. Black

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics.

Philipp Hennig, Søren Hauberg

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Unscented Kalman Filtering on Riemannian Manifolds.

Søren Hauberg, François Lauze, Kim Steenstrup Pedersen

J. Math. Imaging Vis., 2013

Probabilistic Numerical Analysis in Riemannian Statistics.

Philipp Hennig, Søren Hauberg

CoRR, 2013

2012

Natural metrics and least-committed priors for articulated tracking.

Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen

Image Vis. Comput., 2012

A Geometric take on Metric Learning.

Søren Hauberg, Oren Freifeld, Michael J. Black

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Spatial Measures between Human Poses for Classification and Understanding.

Søren Hauberg, Kim Steenstrup Pedersen

Proceedings of the Articulated Motion and Deformable Objects, 2012

2011

Predicting Articulated Human Motion from Spatial Processes.

Søren Hauberg, Kim Steenstrup Pedersen

Int. J. Comput. Vis., 2011

Unscented Kalman Filtering for Articulated Human Tracking.

Anders Boesen Lindbo Larsen, Søren Hauberg, Kim Steenstrup Pedersen

Proceedings of the Image Analysis - 17th Scandinavian Conference, 2011

Means in spaces of tree-like shapes.

Aasa Feragen, Søren Hauberg, Mads Nielsen, François Lauze

Proceedings of the IEEE International Conference on Computer Vision, 2011

An Empirical Study on the Performance of Spectral Manifold Learning Techniques.

Peter Mysling, Søren Hauberg, Kim Steenstrup Pedersen

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Data-Driven Importance Distributions for Articulated Tracking.

Søren Hauberg, Kim Steenstrup Pedersen

Proceedings of the Energy Minimazation Methods in Computer Vision and Pattern Recognition, 2011

2010

Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations.

Stefan Sommer, François Lauze, Søren Hauberg, Mads Nielsen

Proceedings of the Computer Vision - ECCV 2010, 2010

Gaussian-Like Spatial Priors for Articulated Tracking.

Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen

Proceedings of the Computer Vision, 2010

GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking.

Rune Møllegaard Friborg, Søren Hauberg, Kenny Erleben

Proceedings of the Trends and Topics in Computer Vision, 2010

Stick It! Articulated Tracking Using Spatial Rigid Object Priors.

Søren Hauberg, Kim Steenstrup Pedersen

Proceedings of the Computer Vision - ACCV 2010, 2010

2009

Interactive Inverse Kinematics for Human Motion Estimation.

Morten Engell-Nørregård, Søren Hauberg, Jérôe Lapuyade, Kenny Erleben, Kim Steenstrup Pedersen

Proceedings of the Sixth Workshop on Virtual Reality Interactions and Physical Simulations, 2009

Three Dimensional Monocular Human Motion Analysis in End-Effector Space.

Søren Hauberg, Jérôe Lapuyade, Morten Engell-Nørregård, Kenny Erleben, Kim Steenstrup Pedersen

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2009

2008

Brownian Warps for Non-Rigid Registration.

Mads Nielsen, Peter Johansen, Andrew D. Jackson, Benny Lautrup, Søren Hauberg

J. Math. Imaging Vis., 2008

An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application.

Søren Hauberg, Jakob Sloth

J. Math. Imaging Vis., 2008